Organ-specific backprojection

ABSTRACT

The invention relates to a method for the selective imaging of body structures, in which method—a first image data set is acquired by means of a first tomography method,—a second image data set is acquired by means of a second tomography method which has a resolution which is higher than that of the first method, the image data of the first and the second image data set coinciding at least partly in space,—an image is reconstructed from the first image data set, and—the image data to be imaged is selected from the first image data set by means of the second image data set. In order to achieve a higher imaging quality while using a low-resolution tomography method, in accordance with the invention it is proposed that for the image reconstruction from the first image data set—first at least one image region to be imaged is selected from the second image data set, and—subsequently the image reconstruction is calculated from the image data of the first image data set which are situated in the selected image region.

The invention relates to a method for the selective imaging of bodystructures, in which method

-   -   a first image data set is acquired by means of a first        tomography method,    -   a second image data set is acquired by means of a second        tomography method which has a resolution which is higher than        that of the first method, the image data of the first and the        second image data set coinciding at least partly in space,    -   an image is reconstructed from the first image data set, and    -   the image data to be imaged is selected by means of the second        image data set.

The invention also relates to a device for the selective imaging of bodystructures in conformity with the described method and to a computerprogram which is to be executed on a computer and comprises programmingmeans for executing the described steps of the method.

Many tomography methods, notably tomography methods intended for nuclearmedicine, such as SPECT (Single Photon Emission Computed Tomography) orPET (Positron Emission Tomography) methods, have the advantage that theyprovide the viewer of the tomographically formed image with informationwhich goes beyond pure morphology and that in some cases they alsovisualize physiological processes. Such tomography methods have thedrawback, however, that they have only a low spatial resolution so thatoften only a very poor imaging quality is achieved, notably for finestructures.

In order to avoid this drawback it is known to combine said tomographymethod with a further tomography method. The second tomography methodthen images the same region as the previously described tomographymethod having the low resolution. On the basis of the second tomographymethod, having a higher resolution, the viewer can then select a givenregion of interest from the overall image; very exact selection(so-called segmentation) is then possible because of the high resolutionof the second method. Subsequently, that region of the low-resolutiontomography image, produced by the first, low-resolution tomographymethod, which corresponds to the selected region of the high-resolutiontomographic image is associated therewith by way of image registration,and exclusively this region is imaged. A method of this kind isdescribed in the article “Iterative Reconstruction of EmissionTomography Data with A Priori Information”, Vollmar St. et al.,Transactions on Medical Imaging, 199.

This type of combination of two tomography methods has the drawback thatthe original image acquired by means of the low-resolution tomographymethod is reconstructed in a conventional manner and that the selectionof a detail of this image by means of the high-resolution method takesplace only at a later stage. For the conventional reconstruction of theimage, the acquired image data are backprojected regularly; during suchbackprojection the signals measured during the image acquisition by wayof forward projection are distributed along the relevant projection lineacross the entire image region. Because of this distribution across theentire image region, the signals become unsharp and thedistance-to-noise ratio becomes small. Experts in this field refer tothis phenomenon as “smearing”.

Such smearing is particularly disadvantageous when an iterative methodis used for the backprojection, because the smearing and the large imageregion to be measured necessitate a large number of iterations, thusprolonging the required calculation time and effort.

Therefore, it is an object of the invention to provide a method whichenables a higher imaging quality to be achieved for a low-resolutiontomography method. It is also an object of the invention to provide adevice and a computer program for carrying out said method.

The object is achieved in accordance with the invention in that for theimage reconstruction from the first image data set

-   -   first at least one image region to be imaged is selected from        the second image data set, and    -   subsequently the image reconstruction is calculated from the        image data of the first image data set which are situated in the        selected image region.

Therefore, the method in accordance with the invention does notcalculate a backprojection across the entire image region during theimage reconstruction. Instead, an image region which is of interest tothe viewer is selected in advance. This selection is performed on thebasis of image data which have been acquired by means of a secondtomography method having a resolution which is higher than that of thefirst tomography method. It is notably possible to select regions of theimage which contain the object to be imaged or parts thereof.Furthermore, it is also possible to select a number of regions which mayalso be coherent, for example, vascular systems.

The backprojection of the image data across the selected image regionensures that the image values are not smeared across the entire imageregion, but only across a smaller image region, that is, the selectedimage region. It is thus achieved that the signal-to-noise ratio (SNR)is increased and the quality of the images of the structures to beimaged is enhanced.

The method in accordance with the invention is advantageous notably whenthe first tomography method is a nuclear-medical tomography method,notably a SPECT method or a PET method. According to such methods, acontrast medium is administered to the patient prior to the tomographicacquisition of the image data. This contrast medium concentrates ingiven structures of the body, possibly in dependence on givenphysiological processes, and is imaged with a high contrast by thenuclear medical tomography method. SPECT and PET then have only a lowspatial resolution of from approximately 5 to 15 mm. In order to enhancethe image quality, use can notably be made of a magnetic resonancetomography method or an X-ray tomography method (MR and CT,respectively). These tomography methods have a resolution in the rangeof from 0.5 to 1 mm. The use of the method in accordance with theinvention is advantageous in particular when a combined CT/PET system oranother tomography apparatus combining other tomographic methods is usedfor the tomographic imaging.

According to an advantageous version of the method the selection of theimage region is performed by means of an automatic segmentation method.

In addition to the manual segmentation by the viewer, for example, bydefining image boundaries or by selecting image corner points, notablyautomatic selection methods are advantageously used. According to theautomatic selection methods, for example, a selection of the imageelements to be imaged can be carried out on the basis of their imagevalues (for example, grey values). For example, it is possible to selectgiven body tissues on the basis of the image values of a computedtomography X-ray image (so-called HU values), said body tissues thenbeing imaged or excluded from imaging. Furthermore, it is feasible foran automatic segmentation method to select regions which have the sameor a similar image value and are coherent. Conventional segmentationmethods, for example, the so-called regional growing method, can then beused. It may also be arranged that other methods, such as morphologicalopening or the like, are used for the automatic selection of an imageregion.

The method in accordance with the invention may ensure in particularthat the necessary association of the image data of the first and thesecond image data set with one another, that is, the so-calledregistration, is simplified or accelerated by associating exclusivelyimage data of the first image data set which are to be imaged with thesecond image data set.

It is particularly advantageous to use the method in accordance with theinvention when the image reconstruction is carried out by way ofiterative backprojection. An iterative calculation then takes place inprinciple in such a manner that the difference is formed betweenintermediate results of an image calculation which is periodicallyperformed in the same manner is formed and that the quality of thecalculated image is evaluated on the basis of the value of thedifference between two successive calculation cycles. Normally speaking,a limit value (convergence criterion) to be reached is then defined.

Because the distance between the signal and the noise value is increasedfrom the very start of the method in accordance with the invention, themethod in accordance with the invention enables a reduction of thenumber of iteration steps required until a convergence criterion is met,that is, in comparison with the conventional method with smearing acrossthe entire image region. Analogously, when the number of iteration stepsin the method in accordance with the invention is kept the same as inconventional methods, the image quality of the image formed by means ofthe method in accordance with the invention can be enhanced incomparison with the image quality of the image reconstructed in aconventional manner.

A further aspect of the invention concerns a device for the selectiveimaging of body structures, which device includes first tomographicimage data acquisition means, second tomographic image data acquisitionmeans, having a resolution which is higher than that of the firsttomographic image data acquisition means, means for image reconstructionby backprojection of an image, notably from a first image data set whichhas been acquired by means of the first tomographic image dataacquisition means, and selection means for selecting at least one regionof the image data to be imaged, preferably by selection of one or moreregions of an image which has been derived from the second image dataset. The backprojection means co-operate with the selection means insuch a manner that during the backprojection of the image dataexclusively the image data are projected which are situated in theselected image region which was selected, by way of the second imagedata set, by the selection means.

Finally, a last aspect of the invention concerns a computer program withprogramming means for making a computer carry out the method of claim 1when the computer program is executed on a computer.

A preferred embodiment of the invention will be described in detailhereinafter with reference to the Figures. Therein:

FIG. 1 shows a flow chart of a method in accordance with the invention,

FIG. 2 is a diagrammatic representation of the co-operation of the meansof a device in accordance with the invention, and

FIG. 3 shows a flow chart of a method for iterative backprojection.

As is shown in FIG. 1, in conformity with the preferred version of themethod in accordance with the invention first a computed tomographyimage S1 of a body region is formed; for this purpose several sliceimages of this body region are acquired at a given distance from oneanother. This computed tomography image yields a CT image data set R1.Before or after the computed tomography image acquisition, a contrastmedium is administered to the patient and a SPECT image S2 is formed,resulting in a SPECT image data set R2. The SPECT image S2 is preferablyformed for the same body region and while using the same distancebetween the slice planes as for the CT image S1.

For the CT image data set R1 and the SPECT image data set R2 there isperformed an image superposition or registration operation S3 in whichthe image data of the CT image data set R1 which are situated in thesame geometrical position as the image data of the SPECT image data setR2 are associated with one another. Known methods, for example, fiducialmarkers can be used for such association. The CT image S1 and the SPECTimage S2 need not necessarily cover an identical image region, but itsuffices when the two images overlap in the region to be imaged.Furthermore, it is not necessary either for the spacing of the slices ofthe two images to be the same; it is also feasible that the distancebetween the slices of one image amounts to an integer multiple of thedistance between the slices of the other image.

An image S4 is then reconstructed from the CT image data set R1;customary methods, such as iterative or analytic backprojection, can beused for this purpose. In the CT image R3 thus formed a segmentation ofthe region S5 to be imaged is performed. This segmentation can takeplace in a direction orthogonal as well as in a direction parallel tothe projection direction, notably simultaneously in both directions. Forexample, a region to be imaged can be defined by setting a plurality ofcorner points of a region to be imaged or by drawing a boundary linearound a region. It is also possible to select a plurality of regions tobe imaged which are connected to one another or not. Furthermore, it isfeasible for the segmentation to be executed automatically by theselection of image elements having a given range of image values or bythe selection of coherent regions having a similar range of imagevalues, for example, by way of the so-called region growing method.Furthermore, it is feasible to select structures in the image which aresmaller or larger than a given value; customary methods, such as themorphological opening method, can be used for this purpose. It is alsofeasible to remove one or more image regions from the region to beimaged by means of a filtering operation.

The segmented CT image R4 thus formed is converted into a segmented CTimage data set R5 by way of a numerical forward projection S6. Duringthis step, the selected image elements, that is, the segmented region tobe imaged, can be associated again with the image data of the originalCT image data set in a simplified manner.

The image data of the segmented CT image data set are associated withthe image data of the SPECT image data set in a next step S7, resultingin a segmented SPECT image data set R6. This segmented SPECT image dataset R6 contains only the image data which are of relevance for theregion to be imaged as selected on the basis of the CT image data set.In a further step S8 an image is reconstructed from the segmented SPECTimage data set, that is, preferably by iterative backprojection of thesegmented SPECT image data set. During this iterative backprojection,the image data is smeared only across the region to be imaged, soregularly across a region which is substantially smaller than theoverall image region, thus enhancing the signal-to-noise ratio. Theimage R7 thus reconstructed has sharper edges and contains morecontrast. This reduces the number of iteration steps required for animage whose quality is substantially equivalent to that of an imageobtained by means of a conventional reconstruction technique, meaningthat the required calculation time and effort are less. Analogously,when the number of iteration steps is the same as that of theconventional method, that is, while spending the same calculation timeand calculation effort, an image of significantly higher quality can beformed.

FIG. 2 is a diagrammatic representation of the construction of thedevice in accordance with the invention and of the programming means ofthe computer program in accordance with the invention.

The device comprises CT image acquisition means M1 and SPECT imageacquisition means M2 which co-operate with image superposition orregistration means M4. The CT image acquisition means M1 co-operate withimage reconstruction means M3 for the CT image, which means form a CTimage from the CT image data set. This CT image is segmented by means ofmanual segmentation means M5 which are controlled by a user of thedevice, thus selecting a region to be image.

The manual segmentation means co-operate with means for the numericalforward projection M7 of the selected CT image elements which form animage data set from the segmented image.

Alternatively, as is denoted by the dashed lines in FIG. 2, the CT imageacquisition means can co-operate with automatic segmentation means M6which automatically select given data on the basis of preset parametersor parameters which can be influenced by the user of the device.

The image data selected by means of the automatic segmentation means M6or the image data produced by means of the numerical forward projectionmeans, co-operate with image reconstruction means M8 for the SPECT imagedata. The image reconstruction means for the SPECT image data co-operatewith the image superposition/registration means so as to associate theselected CT image data with the corresponding, geometrically identicallysituated SPECT image data.

Alternatively it may also be arranged to perform the image superpositionor registration by means of the image superposition means M4 only at aninstant after a manual (M5) or automatic (M6) segmentation, and hencealso selection of the image elements to be imaged, has taken place. Inthat case there is no superposition of image regions or registration ofimage data which are not situated in a region to be imaged.

The image reconstruction means SPECT M8 form a high-quality nuclearmedical image of the segmented image region from the selected imagedata.

The reconstruction of an image from the segmented SPECT image data setS8 by way of iterative backprojection will be described with referenceto FIG. 3. The iteration consists in that first, in a backprojectionS10, an iteration image R11 is calculated by backprojection of the imagedata to be imaged of the first image data set R6, selected on the basisof the second image data set or the image R1, R3, after which aniteration image data set R12 is numerically formed from this iterationimage R11 in a calculation step S11. This iteration image data set R12thus represents the result of a numerical forward projection S11 of thecalculated image. Subsequently, a difference is formed between thenumerically formed iteration image data set R12 and the first image dataset R10. This difference is a measure of the deviation between theiteration image data set R12 and the iteration start image data set R10.If this difference is particularly small, the calculated image does notconstitute a significant qualitative improvement relative to theinitially calculated image. In this case the iterative calculationprocess is terminated and the calculated image R11, R7 is output via anoutput S20.

When the difference does not drop below a predetermined value (theconvergence criterion), however, the difference is added to theiteration image data set S11 and a new iteration start image data setR14 is calculated. Using this calculated iteration start image data setR14, representing the new iteration start mage data set R10,subsequently an iteration operation is started again, at the end ofwhich the difference is again used for evaluating the convergence and,should the converge criterion not be satisfied, the difference is againadded to the iteration image data set R12 so as to form an iterationstart image data set R14.

The above iteration steps are repeated until the convergence criterionis satisfied and the image R11 last calculated is output to the vieweras a segmented SPECT image R7.

1. A method for the selective imaging of body structures, in whichmethod a first image data set is acquired by means of a first tomographymethod, a second image data set is acquired by means of a secondtomography method which has a resolution which is higher than that ofthe first method, the image data of the first and the second image dataset coinciding at least partly in space, an image is reconstructed fromthe first image data set, and the image data to be imaged is selectedfrom the first image data set by means of the second image data set,wherein for the reconstruction from the first image data set first atleast one image region to be imaged is selected from the second imagedata set, and subsequently the image reconstruction is calculated fromthe image data of the first image data set which are situated in theselected image region.
 2. A method as claimed in claim 1, wherein thefirst tomography method is a nuclear medical tomography method, notablySPECT or PET.
 3. A method as claimed in claim 1, wherein the selectionof the image region is performed by means of an automatic segmentationmethod.
 4. A method as claimed in claim 1, wherein the imagereconstruction is carried out by way of iterative backprojection.
 5. Amethod as claimed in claim 4, wherein the calculation of the imageconsists of the initial calculation of an image by backprojection of theimage data to be imaged of the first image data set, the following stepsnumerical formation of an iteration image data set from the calculatedimage, determination of the difference between the first image data setand the iteration image data set, calculation of an iteration image byaddition of the difference to the calculated image, and the iterativerepetition of these steps for the calculated iteration images until atleast one convergence criterion is satisfied, that is, notably thedifference dropping below a predetermined convergence value.
 6. A devicefor the selective imaging of body structures, which device includesfirst tomographic image data acquisition means for the acquisition of afirst image data set, second tomographic image data acquisition meansfor the acquisition of a second image data set, which second tomographicimage data acquisition means have a resolution which is higher than thatof the first tomographic image data acquisition means, backprojectionmeans for image reconstruction of an image from the first image dataset, and selection means for selecting, by means of the second imagedata set, the image data to be imaged, characterized in that thebackprojection means co-operate with the selection means in such amanner that the image is calculated exclusively from the image data ofthe first image data set which are situated in the selected imageregion.
 7. A computer program which includes programming means formaking a computer carry out the method claimed in claim 1 when thecomputer program is executed on a computer.
 8. A method for selectivelyimaging body structures, comprising the steps of: using a firsttomography method to acquire a first image data set; using a secondtomography method to acquire a second image data set, the secondtomography method having a higher resolution than the first tomographymethod and the second image data set containing image data that at leastpartly coincides in space with image data of the first image data set;and reconstructing an image from the first image data set; wherein datafrom the first image set used in the reconstructing set is selectedusing the second data set.
 9. The method of claim 8, wherein thereconstructing step further comprises the steps of: selecting a regionto be imaged from at least one region represented in the second imagedata set; and calculating the image reconstruction from image data in aregion represented in the first data set that corresponds to theselected region represented in the second data set.